{"id":"https://openalex.org/W3189839624","doi":"https://doi.org/10.1109/access.2021.3103763","title":"Beats-to-Beats Estimation of Blood Pressure During Supine Cycling Exercise Using a Probabilistic Nonparametric Method","display_name":"Beats-to-Beats Estimation of Blood Pressure During Supine Cycling Exercise Using a Probabilistic Nonparametric Method","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3189839624","doi":"https://doi.org/10.1109/access.2021.3103763","mag":"3189839624"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3103763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3103763","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09509499.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09509499.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102984513","display_name":"Qing Liu","orcid":"https://orcid.org/0000-0001-9439-2970"},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Liu","raw_affiliation_strings":["School of Advanced Technology, Xi\u2019an Jiaotong\u2013Liverpool University, Suzhou, Jiangsu, China","School of Advanced Technology, Xi'an Jiaotong\u2013Liverpool University, Suzhou, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0001-9439-2970","affiliations":[{"raw_affiliation_string":"School of Advanced Technology, Xi\u2019an Jiaotong\u2013Liverpool University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I69356397"]},{"raw_affiliation_string":"School of Advanced Technology, Xi'an Jiaotong\u2013Liverpool University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075152032","display_name":"Yali Zheng","orcid":"https://orcid.org/0000-0002-6215-1694"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yali Zheng","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070333614","display_name":"Yuan\u2010Ting Zhang","orcid":"https://orcid.org/0000-0003-4150-5470"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuanting Zhang","raw_affiliation_strings":["Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-4150-5470","affiliations":[{"raw_affiliation_string":"Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015802672","display_name":"Carmen C. Y. Poon","orcid":"https://orcid.org/0000-0001-7717-4752"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carmen C. Y. Poon","raw_affiliation_strings":["GMed IT, Ltd., Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7717-4752","affiliations":[{"raw_affiliation_string":"GMed IT, Ltd., Hong Kong","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5807,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.59606631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"115655","last_page":"115663"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11209","display_name":"Cardiovascular and exercise physiology","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.6667284369468689},{"id":"https://openalex.org/keywords/supine-position","display_name":"Supine position","score":0.6193613409996033},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5272295475006104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4695582687854767},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4457879960536957},{"id":"https://openalex.org/keywords/diastole","display_name":"Diastole","score":0.4455106854438782},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4348142147064209},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.41309165954589844},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.40108609199523926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38858404755592346},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38414090871810913},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35981106758117676},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.34085965156555176},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3275737762451172}],"concepts":[{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.6667284369468689},{"id":"https://openalex.org/C125567185","wikidata":"https://www.wikidata.org/wiki/Q3267428","display_name":"Supine position","level":2,"score":0.6193613409996033},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5272295475006104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4695582687854767},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4457879960536957},{"id":"https://openalex.org/C57900726","wikidata":"https://www.wikidata.org/wiki/Q492905","display_name":"Diastole","level":3,"score":0.4455106854438782},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4348142147064209},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.41309165954589844},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.40108609199523926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38858404755592346},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38414090871810913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35981106758117676},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.34085965156555176},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3275737762451172}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3103763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3103763","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09509499.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/8f52a5b8-69a7-4b22-ba2e-b9b7d4070741","is_oa":true,"landing_page_url":"https://scholars.cityu.edu.hk/en/publications/8f52a5b8-69a7-4b22-ba2e-b9b7d4070741","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, Q, Zheng, Y, Zhang, Y & Poon, C C Y 2021, 'Beats-to-Beats Estimation of Blood Pressure during Supine Cycling Exercise Using a Probabilistic Nonparametric Method', IEEE Access, vol. 9, 9509499, pp. 115655-115663. https://doi.org/10.1109/ACCESS.2021.3103763","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:5a720d4b9fba44f089396d1b6395875d","is_oa":true,"landing_page_url":"https://doaj.org/article/5a720d4b9fba44f089396d1b6395875d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 115655-115663 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3103763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3103763","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09509499.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.800000011920929}],"awards":[{"id":"https://openalex.org/G5849031524","display_name":null,"funder_award_id":"18KJB416007","funder_id":"https://openalex.org/F4320335440","funder_display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China"},{"id":"https://openalex.org/G6310107755","display_name":null,"funder_award_id":"JCYJ20190813111001769","funder_id":"https://openalex.org/F4320329791","funder_display_name":"Shenzhen Fundamental Research Program"},{"id":"https://openalex.org/G7862576746","display_name":null,"funder_award_id":"2020110","funder_id":"https://openalex.org/F4320319297","funder_display_name":"Shenzhen Technology University"}],"funders":[{"id":"https://openalex.org/F4320319297","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27"},{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"},{"id":"https://openalex.org/F4320329791","display_name":"Shenzhen Fundamental Research Program","ror":null},{"id":"https://openalex.org/F4320335440","display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3189839624.pdf","grobid_xml":"https://content.openalex.org/works/W3189839624.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1933258993","https://openalex.org/W1967852667","https://openalex.org/W1969600128","https://openalex.org/W1985034572","https://openalex.org/W1996783892","https://openalex.org/W2017271435","https://openalex.org/W2059208589","https://openalex.org/W2083872334","https://openalex.org/W2151950656","https://openalex.org/W2154467145","https://openalex.org/W2167925220","https://openalex.org/W2183841542","https://openalex.org/W2292374408","https://openalex.org/W2294418644","https://openalex.org/W2338236284","https://openalex.org/W2431637923","https://openalex.org/W2475064587","https://openalex.org/W2506321621","https://openalex.org/W2514523036","https://openalex.org/W2555230379","https://openalex.org/W2608498389","https://openalex.org/W2790680409","https://openalex.org/W2896545929","https://openalex.org/W3030350170","https://openalex.org/W3042891861","https://openalex.org/W3047559810","https://openalex.org/W3101824250","https://openalex.org/W3150595609","https://openalex.org/W4211049957","https://openalex.org/W4237588818","https://openalex.org/W6684913695"],"related_works":["https://openalex.org/W3001160440","https://openalex.org/W2334516142","https://openalex.org/W3200205987","https://openalex.org/W3126470155","https://openalex.org/W2130742338","https://openalex.org/W1967939705","https://openalex.org/W2064736843","https://openalex.org/W2528189326","https://openalex.org/W2106758714","https://openalex.org/W2734294398"],"abstract_inverted_index":{"Blood":[0],"pressure":[1],"(BP)":[2],"is":[3],"an":[4],"important":[5],"clinical":[6],"vital":[7],"sign":[8],"that":[9],"varies":[10],"from":[11,52,68,181,188],"beat-to-beat.":[12],"Nevertheless,":[13],"these":[14],"variations":[15],"cannot":[16],"be":[17],"captured":[18],"by":[19,49],"the":[20,36,125,135,203,213],"conventional":[21],"cuff-based":[22],"BP":[23,40,44,95],"monitors.":[24],"This":[25],"study":[26],"proposes":[27],"and":[28,42,102,114,128,133,152,157,174,187,196,207,219],"evaluates":[29],"novel":[30],"cuffless":[31],"frameworks":[32],"to":[33,118,184,191],"continuously":[34,113],"estimate":[35],"10-beat":[37,126,214],"averaged":[38],"systolic":[39],"(SBP)":[41],"diastolic":[43],"(DBP)":[45],"during":[46,132],"dynamic":[47,230],"exercise":[48,80],"fusing":[50],"information":[51],"multiple":[53,163],"biosensors":[54],"using":[55],"five":[56,119],"machine":[57,120,177],"learning":[58,121],"algorithms.":[59],"Over":[60],"100":[61],"thousand":[62],"beats":[63],"of":[64,86,143,162,171,216],"data":[65],"were":[66,97,111],"collected":[67],"62":[69],"subjects":[70],"(aged":[71],"59":[72],"\u00b1":[73],"10":[74],"years),":[75],"each":[76,89],"underwent":[77],"a":[78,222,225],"maximal":[79],"stress":[81],"test.":[82],"The":[83,94,138,160,199],"average":[84],"length":[85],"recording":[87],"for":[88,100,105,123,155,194],"subject":[90],"was":[91,149],"35":[92],"minutes.":[93],"ranges":[96],"75-280":[98],"mmHg":[99,104,151,154,183,186,190,193],"SBP":[101,127,156,195,218],"36-157":[103],"DBP":[106,129,220],"respectively.":[107,159,198],"Multiple":[108],"physiological":[109],"parameters":[110],"measured":[112],"used":[115],"as":[116],"inputs":[117],"algorithms":[122],"estimating":[124,212],"averages":[130,215],"before,":[131],"after":[134],"cycling":[136],"exercise.":[137],"mean":[139],"absolute":[140],"error":[141],"(MAE)":[142],"Gaussian":[144],"process":[145],"regression":[146,165,167],"(GPR)":[147],"model":[148,201],"4.8":[150],"3.4":[153],"DBP,":[158,197],"MAE":[161],"linear":[164],"(MLR),":[166],"tree":[168],"(RT),":[169],"ensemble":[170],"trees":[172],"(ETs),":[173],"support":[175],"vector":[176],"(SVM)":[178],"models":[179,206],"varied":[180],"6.1":[182],"17.6":[185],"4.0":[189],"9.7":[192],"GPR":[200],"outperformed":[202],"other":[204],"four":[205],"showed":[208],"promising":[209],"results":[210],"in":[211,224],"both":[217],"without":[221],"cuff":[223],"general":[226],"elderly":[227],"population":[228],"under":[229],"conditions.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
